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<a href="#pub-types">Public Types</a> &#124;
<a href="#pub-methods">Public Member Functions</a> &#124;
<a href="#pub-static-methods">Static Public Member Functions</a> &#124;
<a href="#pro-methods">Protected Member Functions</a> &#124;
<a href="#pro-attribs">Protected Attributes</a> &#124;
<a href="classimageNet-members.html">List of all members</a>  </div>
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<div class="title">imageNet Class Reference<div class="ingroups"><a class="el" href="group__deepVision.html">DNN Vision Library (jetson-inference)</a> &raquo; <a class="el" href="group__imageNet.html">imageNet</a></div></div>  </div>
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<p>Image recognition with classification networks, using TensorRT.  
 <a href="classimageNet.html#details">More...</a></p>

<p><code>#include &lt;<a class="el" href="imageNet_8h_source.html">imageNet.h</a>&gt;</code></p>
<div class="dynheader">
Inheritance diagram for imageNet:</div>
<div class="dyncontent">
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  <img src="classimageNet.png" usemap="#imageNet_map" alt=""/>
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<area href="classtensorNet.html" title="Abstract class for loading a tensor network with TensorRT. " alt="tensorNet" shape="rect" coords="0,0,66,24"/>
</map>
 </div></div>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
Public Types</h2></td></tr>
<tr class="memitem:a0b7e93af566fe96bfc58cda5f4503470"><td class="memItemLeft" align="right" valign="top">enum &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470">NetworkType</a> { <br />
&#160;&#160;<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470a9237dcd407a6df5b51f027b47053b013">CUSTOM</a>, 
<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470a3e774168f30b16946773a737a6c354cf">ALEXNET</a>, 
<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470ab013750d9b65eacdae3c587dd42550c0">GOOGLENET</a>, 
<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470af4a7d4831db43dda4de80c2a395f3ebb">GOOGLENET_12</a>, 
<br />
&#160;&#160;<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470a41ccbd9480e0072ed579da95eb6a479d">RESNET_18</a>, 
<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470aa940343d369f0026258f0a42188a405b">RESNET_50</a>, 
<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470a3bc3f084f3ef071585caf9629e64e24b">RESNET_101</a>, 
<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470a91e56faa59f440c7aeb42f37363f27c4">RESNET_152</a>, 
<br />
&#160;&#160;<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470a4a1ff14a90c30b505d6a2e563ad02bdc">VGG_16</a>, 
<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470ab44362ca647faaeb0b4a3124aef6a6fa">VGG_19</a>, 
<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470a196d67c5fe33ca0e6724b0dfdff0a8e0">INCEPTION_V4</a>
<br />
 }<tr class="memdesc:a0b7e93af566fe96bfc58cda5f4503470"><td class="mdescLeft">&#160;</td><td class="mdescRight">Network choice enumeration.  <a href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470">More...</a><br /></td></tr>
</td></tr>
<tr class="separator:a0b7e93af566fe96bfc58cda5f4503470"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:af6bd86e81ff9e67ffe19b575c17ed104"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#af6bd86e81ff9e67ffe19b575c17ed104">~imageNet</a> ()</td></tr>
<tr class="memdesc:af6bd86e81ff9e67ffe19b575c17ed104"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destroy.  <a href="#af6bd86e81ff9e67ffe19b575c17ed104">More...</a><br /></td></tr>
<tr class="separator:af6bd86e81ff9e67ffe19b575c17ed104"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a11d6b18e0036ef5a329192f8b659dff9"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a11d6b18e0036ef5a329192f8b659dff9">Classify</a> (float *rgba, uint32_t width, uint32_t height, float *confidence=NULL)</td></tr>
<tr class="memdesc:a11d6b18e0036ef5a329192f8b659dff9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Determine the maximum likelihood image class.  <a href="#a11d6b18e0036ef5a329192f8b659dff9">More...</a><br /></td></tr>
<tr class="separator:a11d6b18e0036ef5a329192f8b659dff9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4295a052e7e4d12a369107a6525017a3"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a4295a052e7e4d12a369107a6525017a3">Classify</a> (float *confidence=NULL)</td></tr>
<tr class="memdesc:a4295a052e7e4d12a369107a6525017a3"><td class="mdescLeft">&#160;</td><td class="mdescRight">Determine the maximum likelihood image class.  <a href="#a4295a052e7e4d12a369107a6525017a3">More...</a><br /></td></tr>
<tr class="separator:a4295a052e7e4d12a369107a6525017a3"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a83c68fbe0faab1e88abf07f7b535b8b9"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a83c68fbe0faab1e88abf07f7b535b8b9">PreProcess</a> (float *rgba, uint32_t width, uint32_t height)</td></tr>
<tr class="memdesc:a83c68fbe0faab1e88abf07f7b535b8b9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Perform pre-processing on the image to apply mean-value subtraction and to organize the data into NCHW format and BGR colorspace that the networks expect.  <a href="#a83c68fbe0faab1e88abf07f7b535b8b9">More...</a><br /></td></tr>
<tr class="separator:a83c68fbe0faab1e88abf07f7b535b8b9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad9eb86e82a3a2a05700e3c36f9554e64"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#ad9eb86e82a3a2a05700e3c36f9554e64">Process</a> ()</td></tr>
<tr class="memdesc:ad9eb86e82a3a2a05700e3c36f9554e64"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classProcess.html" title="Static functions for retrieving information about the running process. ">Process</a> the network, without determining the classification argmax.  <a href="#ad9eb86e82a3a2a05700e3c36f9554e64">More...</a><br /></td></tr>
<tr class="separator:ad9eb86e82a3a2a05700e3c36f9554e64"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a478f25126524a256e81ec264aad7e27a"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a478f25126524a256e81ec264aad7e27a">GetNumClasses</a> () const</td></tr>
<tr class="memdesc:a478f25126524a256e81ec264aad7e27a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the number of image recognition classes (typically 1000)  <a href="#a478f25126524a256e81ec264aad7e27a">More...</a><br /></td></tr>
<tr class="separator:a478f25126524a256e81ec264aad7e27a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a42ce2aeeb96379bd04d94f65d483ece1"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a42ce2aeeb96379bd04d94f65d483ece1">GetClassDesc</a> (uint32_t index) const</td></tr>
<tr class="memdesc:a42ce2aeeb96379bd04d94f65d483ece1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the description of a particular class.  <a href="#a42ce2aeeb96379bd04d94f65d483ece1">More...</a><br /></td></tr>
<tr class="separator:a42ce2aeeb96379bd04d94f65d483ece1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a343bbe0aad580411900f811f30e8cbf7"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a343bbe0aad580411900f811f30e8cbf7">GetClassSynset</a> (uint32_t index) const</td></tr>
<tr class="memdesc:a343bbe0aad580411900f811f30e8cbf7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the class synset category of a particular class.  <a href="#a343bbe0aad580411900f811f30e8cbf7">More...</a><br /></td></tr>
<tr class="separator:a343bbe0aad580411900f811f30e8cbf7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a04276f915b0f40d6257cbed3fe47dc5f"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a04276f915b0f40d6257cbed3fe47dc5f">GetClassPath</a> () const</td></tr>
<tr class="memdesc:a04276f915b0f40d6257cbed3fe47dc5f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the path to the file containing the class descriptions.  <a href="#a04276f915b0f40d6257cbed3fe47dc5f">More...</a><br /></td></tr>
<tr class="separator:a04276f915b0f40d6257cbed3fe47dc5f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad0cde8f64f32a50984c947dc823de04e"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470">NetworkType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#ad0cde8f64f32a50984c947dc823de04e">GetNetworkType</a> () const</td></tr>
<tr class="memdesc:ad0cde8f64f32a50984c947dc823de04e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the network type (alexnet or googlenet)  <a href="#ad0cde8f64f32a50984c947dc823de04e">More...</a><br /></td></tr>
<tr class="separator:ad0cde8f64f32a50984c947dc823de04e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a359ecefb8ac20cd44fddc69d38bde3ef"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a359ecefb8ac20cd44fddc69d38bde3ef">GetNetworkName</a> () const</td></tr>
<tr class="memdesc:a359ecefb8ac20cd44fddc69d38bde3ef"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve a string describing the network name.  <a href="#a359ecefb8ac20cd44fddc69d38bde3ef">More...</a><br /></td></tr>
<tr class="separator:a359ecefb8ac20cd44fddc69d38bde3ef"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classtensorNet"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classtensorNet')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classtensorNet.html">tensorNet</a></td></tr>
<tr class="memitem:ad19aafbfa262f9b8ffb0bff561f4d7f7 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ad19aafbfa262f9b8ffb0bff561f4d7f7">~tensorNet</a> ()</td></tr>
<tr class="memdesc:ad19aafbfa262f9b8ffb0bff561f4d7f7 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destory.  <a href="classtensorNet.html#ad19aafbfa262f9b8ffb0bff561f4d7f7">More...</a><br /></td></tr>
<tr class="separator:ad19aafbfa262f9b8ffb0bff561f4d7f7 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2e63d4670461814bd863ee0d9bd41526 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2e63d4670461814bd863ee0d9bd41526">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean=NULL, const char *input_blob=&quot;data&quot;, const char *output_blob=&quot;prob&quot;, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a2e63d4670461814bd863ee0d9bd41526 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance.  <a href="classtensorNet.html#a2e63d4670461814bd863ee0d9bd41526">More...</a><br /></td></tr>
<tr class="separator:a2e63d4670461814bd863ee0d9bd41526 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0a06ffd12b465f39160f4a6925cccd9f inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a0a06ffd12b465f39160f4a6925cccd9f">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean, const char *input_blob, const std::vector&lt; std::string &gt; &amp;output_blobs, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a0a06ffd12b465f39160f4a6925cccd9f inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance with multiple output layers.  <a href="classtensorNet.html#a0a06ffd12b465f39160f4a6925cccd9f">More...</a><br /></td></tr>
<tr class="separator:a0a06ffd12b465f39160f4a6925cccd9f inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a168c7f75c9fd6d264afd016e144f3878 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a168c7f75c9fd6d264afd016e144f3878">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean, const char *input_blob, const <a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> &amp;input_dims, const std::vector&lt; std::string &gt; &amp;output_blobs, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a168c7f75c9fd6d264afd016e144f3878 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance (this variant is used for UFF models)  <a href="classtensorNet.html#a168c7f75c9fd6d264afd016e144f3878">More...</a><br /></td></tr>
<tr class="separator:a168c7f75c9fd6d264afd016e144f3878 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3413eb0ad4f240f457f192f39e2e03e8 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a3413eb0ad4f240f457f192f39e2e03e8">EnableLayerProfiler</a> ()</td></tr>
<tr class="memdesc:a3413eb0ad4f240f457f192f39e2e03e8 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Manually enable layer profiling times.  <a href="classtensorNet.html#a3413eb0ad4f240f457f192f39e2e03e8">More...</a><br /></td></tr>
<tr class="separator:a3413eb0ad4f240f457f192f39e2e03e8 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae49f74ff83e46112a30318fa0576cace inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae49f74ff83e46112a30318fa0576cace">EnableDebug</a> ()</td></tr>
<tr class="memdesc:ae49f74ff83e46112a30318fa0576cace inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Manually enable debug messages and synchronization.  <a href="classtensorNet.html#ae49f74ff83e46112a30318fa0576cace">More...</a><br /></td></tr>
<tr class="separator:ae49f74ff83e46112a30318fa0576cace inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7d0ec0d8504ac8b26c5ab4a6136599ca inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7d0ec0d8504ac8b26c5ab4a6136599ca">AllowGPUFallback</a> () const</td></tr>
<tr class="memdesc:a7d0ec0d8504ac8b26c5ab4a6136599ca inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return true if GPU fallback is enabled.  <a href="classtensorNet.html#a7d0ec0d8504ac8b26c5ab4a6136599ca">More...</a><br /></td></tr>
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<tr class="memitem:a92bb737172d26bda5f67d15346a02514 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a92bb737172d26bda5f67d15346a02514">GetDevice</a> () const</td></tr>
<tr class="memdesc:a92bb737172d26bda5f67d15346a02514 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the device being used for execution.  <a href="classtensorNet.html#a92bb737172d26bda5f67d15346a02514">More...</a><br /></td></tr>
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<tr class="memitem:afb38b5f171025e987a00214cc4379ca9 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#afb38b5f171025e987a00214cc4379ca9">GetPrecision</a> () const</td></tr>
<tr class="memdesc:afb38b5f171025e987a00214cc4379ca9 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the type of precision being used.  <a href="classtensorNet.html#afb38b5f171025e987a00214cc4379ca9">More...</a><br /></td></tr>
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<tr class="memitem:a6b8e8dba05bc5c677027913d8c64f259 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a6b8e8dba05bc5c677027913d8c64f259">IsPrecision</a> (<a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> type) const</td></tr>
<tr class="memdesc:a6b8e8dba05bc5c677027913d8c64f259 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Check if a particular precision is being used.  <a href="classtensorNet.html#a6b8e8dba05bc5c677027913d8c64f259">More...</a><br /></td></tr>
<tr class="separator:a6b8e8dba05bc5c677027913d8c64f259 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a34e350ec6185277ac09ae55a79403e62 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">cudaStream_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a34e350ec6185277ac09ae55a79403e62">GetStream</a> () const</td></tr>
<tr class="memdesc:a34e350ec6185277ac09ae55a79403e62 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the stream that the device is operating on.  <a href="classtensorNet.html#a34e350ec6185277ac09ae55a79403e62">More...</a><br /></td></tr>
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<tr class="memitem:a78cecfb7505be0ea59d29041abc85cbb inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">cudaStream_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a78cecfb7505be0ea59d29041abc85cbb">CreateStream</a> (bool nonBlocking=true)</td></tr>
<tr class="memdesc:a78cecfb7505be0ea59d29041abc85cbb inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Create and use a new stream for execution.  <a href="classtensorNet.html#a78cecfb7505be0ea59d29041abc85cbb">More...</a><br /></td></tr>
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<tr class="memitem:a679b177784c85bfdba63dcd1008ff633 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a679b177784c85bfdba63dcd1008ff633">SetStream</a> (cudaStream_t stream)</td></tr>
<tr class="memdesc:a679b177784c85bfdba63dcd1008ff633 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the stream that the device is operating on.  <a href="classtensorNet.html#a679b177784c85bfdba63dcd1008ff633">More...</a><br /></td></tr>
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<tr class="memitem:a624881afe27acd2b2fff0f0f75308ea2 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a624881afe27acd2b2fff0f0f75308ea2">GetPrototxtPath</a> () const</td></tr>
<tr class="memdesc:a624881afe27acd2b2fff0f0f75308ea2 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the path to the network prototxt file.  <a href="classtensorNet.html#a624881afe27acd2b2fff0f0f75308ea2">More...</a><br /></td></tr>
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<tr class="memitem:ac74d7f0571b7782b945ff85fd6894044 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac74d7f0571b7782b945ff85fd6894044">GetModelPath</a> () const</td></tr>
<tr class="memdesc:ac74d7f0571b7782b945ff85fd6894044 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the path to the network model file.  <a href="classtensorNet.html#ac74d7f0571b7782b945ff85fd6894044">More...</a><br /></td></tr>
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<tr class="memitem:acfa7f1f01b46f658ffc96f8a002e8d48 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#acfa7f1f01b46f658ffc96f8a002e8d48">GetModelType</a> () const</td></tr>
<tr class="memdesc:acfa7f1f01b46f658ffc96f8a002e8d48 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the format of the network model.  <a href="classtensorNet.html#acfa7f1f01b46f658ffc96f8a002e8d48">More...</a><br /></td></tr>
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<tr class="memitem:a0a09d691ea080bd9734c5782c8fff6fd inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a0a09d691ea080bd9734c5782c8fff6fd">IsModelType</a> (<a class="el" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a> type) const</td></tr>
<tr class="memdesc:a0a09d691ea080bd9734c5782c8fff6fd inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return true if the model is of the specified format.  <a href="classtensorNet.html#a0a09d691ea080bd9734c5782c8fff6fd">More...</a><br /></td></tr>
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<tr class="memitem:a9dd2db089176ae6878e9ea7dd8fd80c3 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a9dd2db089176ae6878e9ea7dd8fd80c3">GetNetworkFPS</a> ()</td></tr>
<tr class="memdesc:a9dd2db089176ae6878e9ea7dd8fd80c3 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the network frames per second (FPS).  <a href="classtensorNet.html#a9dd2db089176ae6878e9ea7dd8fd80c3">More...</a><br /></td></tr>
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<tr class="memitem:a49faef5920860345e503023b7c84423c inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a49faef5920860345e503023b7c84423c">GetNetworkTime</a> ()</td></tr>
<tr class="memdesc:a49faef5920860345e503023b7c84423c inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the network runtime (in milliseconds).  <a href="classtensorNet.html#a49faef5920860345e503023b7c84423c">More...</a><br /></td></tr>
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<tr class="memitem:ad266f93035a80dca80cd84d971e4f69b inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float2&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ad266f93035a80dca80cd84d971e4f69b">GetProfilerTime</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:ad266f93035a80dca80cd84d971e4f69b inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the profiler runtime (in milliseconds).  <a href="classtensorNet.html#ad266f93035a80dca80cd84d971e4f69b">More...</a><br /></td></tr>
<tr class="separator:ad266f93035a80dca80cd84d971e4f69b inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a27cf81b3fecf93d2e63a61220a54b393 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a27cf81b3fecf93d2e63a61220a54b393">GetProfilerTime</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query, <a class="el" href="group__tensorNet.html#gaaa4127ed22c7165a32d0474ebf97975e">profilerDevice</a> device)</td></tr>
<tr class="memdesc:a27cf81b3fecf93d2e63a61220a54b393 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the profiler runtime (in milliseconds).  <a href="classtensorNet.html#a27cf81b3fecf93d2e63a61220a54b393">More...</a><br /></td></tr>
<tr class="separator:a27cf81b3fecf93d2e63a61220a54b393 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afc0f50abcf6ac71e96d51eba3ed53d4b inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#afc0f50abcf6ac71e96d51eba3ed53d4b">PrintProfilerTimes</a> ()</td></tr>
<tr class="memdesc:afc0f50abcf6ac71e96d51eba3ed53d4b inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Print the profiler times (in millseconds).  <a href="classtensorNet.html#afc0f50abcf6ac71e96d51eba3ed53d4b">More...</a><br /></td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
Static Public Member Functions</h2></td></tr>
<tr class="memitem:a911888acec5ff79f63e42ecdaed4d9c5"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470">NetworkType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a911888acec5ff79f63e42ecdaed4d9c5">NetworkTypeFromStr</a> (const char *model_name)</td></tr>
<tr class="memdesc:a911888acec5ff79f63e42ecdaed4d9c5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Parse a string to one of the built-in pretrained models.  <a href="#a911888acec5ff79f63e42ecdaed4d9c5">More...</a><br /></td></tr>
<tr class="separator:a911888acec5ff79f63e42ecdaed4d9c5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0a6ed78a812c2c8847aec7e2c9c7ecab"><td class="memItemLeft" align="right" valign="top">static const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a0a6ed78a812c2c8847aec7e2c9c7ecab">NetworkTypeToStr</a> (<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470">NetworkType</a> network)</td></tr>
<tr class="memdesc:a0a6ed78a812c2c8847aec7e2c9c7ecab"><td class="mdescLeft">&#160;</td><td class="mdescRight">Convert a NetworkType enum to a string.  <a href="#a0a6ed78a812c2c8847aec7e2c9c7ecab">More...</a><br /></td></tr>
<tr class="separator:a0a6ed78a812c2c8847aec7e2c9c7ecab"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a27823449de3babc8b6eff1e916aff745"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classimageNet.html">imageNet</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a27823449de3babc8b6eff1e916aff745">Create</a> (<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470">NetworkType</a> networkType=<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470ab013750d9b65eacdae3c587dd42550c0">GOOGLENET</a>, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true)</td></tr>
<tr class="memdesc:a27823449de3babc8b6eff1e916aff745"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance.  <a href="#a27823449de3babc8b6eff1e916aff745">More...</a><br /></td></tr>
<tr class="separator:a27823449de3babc8b6eff1e916aff745"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9da8ad51bde43449ea159607ee97bb43"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classimageNet.html">imageNet</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a9da8ad51bde43449ea159607ee97bb43">Create</a> (const char *prototxt_path, const char *model_path, const char *mean_binary, const char *class_labels, const char *input=<a class="el" href="group__imageNet.html#ga00bb3120ef3040793ad3ee25d2727f5b">IMAGENET_DEFAULT_INPUT</a>, const char *output=<a class="el" href="group__imageNet.html#ga74a585b96a1bd960b5201f6b69752fad">IMAGENET_DEFAULT_OUTPUT</a>, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true)</td></tr>
<tr class="memdesc:a9da8ad51bde43449ea159607ee97bb43"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance.  <a href="#a9da8ad51bde43449ea159607ee97bb43">More...</a><br /></td></tr>
<tr class="separator:a9da8ad51bde43449ea159607ee97bb43"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a84b96993a80be279067e0508f649e602"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classimageNet.html">imageNet</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a84b96993a80be279067e0508f649e602">Create</a> (int argc, char **argv)</td></tr>
<tr class="memdesc:a84b96993a80be279067e0508f649e602"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance by parsing the command line.  <a href="#a84b96993a80be279067e0508f649e602">More...</a><br /></td></tr>
<tr class="separator:a84b96993a80be279067e0508f649e602"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7629a888728ef94bf35e573a96ebe4bd"><td class="memItemLeft" align="right" valign="top">static const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a7629a888728ef94bf35e573a96ebe4bd">Usage</a> ()</td></tr>
<tr class="memdesc:a7629a888728ef94bf35e573a96ebe4bd"><td class="mdescLeft">&#160;</td><td class="mdescRight">Usage string for command line arguments to <a class="el" href="classimageNet.html#a27823449de3babc8b6eff1e916aff745" title="Load a new network instance. ">Create()</a>  <a href="#a7629a888728ef94bf35e573a96ebe4bd">More...</a><br /></td></tr>
<tr class="separator:a7629a888728ef94bf35e573a96ebe4bd"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a874e53e6172211c555031e50c6391f98"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a874e53e6172211c555031e50c6391f98">LoadClassInfo</a> (const char *filename, std::vector&lt; std::string &gt; &amp;descriptions, int expectedClasses=-1)</td></tr>
<tr class="memdesc:a874e53e6172211c555031e50c6391f98"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load class descriptions from a label file.  <a href="#a874e53e6172211c555031e50c6391f98">More...</a><br /></td></tr>
<tr class="separator:a874e53e6172211c555031e50c6391f98"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab21eae64422a301712bf84252ede634d"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#ab21eae64422a301712bf84252ede634d">LoadClassInfo</a> (const char *filename, std::vector&lt; std::string &gt; &amp;descriptions, std::vector&lt; std::string &gt; &amp;synsets, int expectedClasses=-1)</td></tr>
<tr class="memdesc:ab21eae64422a301712bf84252ede634d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load class descriptions and synset strings from a label file.  <a href="#ab21eae64422a301712bf84252ede634d">More...</a><br /></td></tr>
<tr class="separator:ab21eae64422a301712bf84252ede634d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_static_methods_classtensorNet"><td colspan="2" onclick="javascript:toggleInherit('pub_static_methods_classtensorNet')"><img src="closed.png" alt="-"/>&#160;Static Public Member Functions inherited from <a class="el" href="classtensorNet.html">tensorNet</a></td></tr>
<tr class="memitem:abe33fae5332296e2d917cb4ce435e255 inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#abe33fae5332296e2d917cb4ce435e255">FindFastestPrecision</a> (<a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowInt8=true)</td></tr>
<tr class="memdesc:abe33fae5332296e2d917cb4ce435e255 inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Determine the fastest native precision on a device.  <a href="classtensorNet.html#abe33fae5332296e2d917cb4ce435e255">More...</a><br /></td></tr>
<tr class="separator:abe33fae5332296e2d917cb4ce435e255 inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae88436e652afdd7bceef7cb7c5fde7a6 inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static std::vector&lt; <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae88436e652afdd7bceef7cb7c5fde7a6">DetectNativePrecisions</a> (<a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>)</td></tr>
<tr class="memdesc:ae88436e652afdd7bceef7cb7c5fde7a6 inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Detect the precisions supported natively on a device.  <a href="classtensorNet.html#ae88436e652afdd7bceef7cb7c5fde7a6">More...</a><br /></td></tr>
<tr class="separator:ae88436e652afdd7bceef7cb7c5fde7a6 inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa3bf1a3bf1fca38b39a200b4d8f727b2 inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#aa3bf1a3bf1fca38b39a200b4d8f727b2">DetectNativePrecision</a> (const std::vector&lt; <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> &gt; &amp;nativeTypes, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> type)</td></tr>
<tr class="memdesc:aa3bf1a3bf1fca38b39a200b4d8f727b2 inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Detect if a particular precision is supported natively.  <a href="classtensorNet.html#aa3bf1a3bf1fca38b39a200b4d8f727b2">More...</a><br /></td></tr>
<tr class="separator:aa3bf1a3bf1fca38b39a200b4d8f727b2 inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7d72ec8bbaf61278ce533afd60d5391c inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7d72ec8bbaf61278ce533afd60d5391c">DetectNativePrecision</a> (<a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>)</td></tr>
<tr class="memdesc:a7d72ec8bbaf61278ce533afd60d5391c inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Detect if a particular precision is supported natively.  <a href="classtensorNet.html#a7d72ec8bbaf61278ce533afd60d5391c">More...</a><br /></td></tr>
<tr class="separator:a7d72ec8bbaf61278ce533afd60d5391c inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-methods"></a>
Protected Member Functions</h2></td></tr>
<tr class="memitem:a0ea17be1ce78b3e0758af46c970a968c"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a0ea17be1ce78b3e0758af46c970a968c">imageNet</a> ()</td></tr>
<tr class="separator:a0ea17be1ce78b3e0758af46c970a968c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a84dd4bae637b43560c6a1ca71e1df3fe"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a84dd4bae637b43560c6a1ca71e1df3fe">init</a> (<a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470">NetworkType</a> networkType, uint32_t maxBatchSize, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device, bool allowGPUFallback)</td></tr>
<tr class="separator:a84dd4bae637b43560c6a1ca71e1df3fe"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa5321e8082e2dc35f5982882fa284181"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#aa5321e8082e2dc35f5982882fa284181">init</a> (const char *prototxt_path, const char *model_path, const char *mean_binary, const char *class_path, const char *input, const char *output, uint32_t maxBatchSize, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device, bool allowGPUFallback)</td></tr>
<tr class="separator:aa5321e8082e2dc35f5982882fa284181"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6beef2c8d0972eaadad37abc89e74f95"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a6beef2c8d0972eaadad37abc89e74f95">loadClassInfo</a> (const char *filename, int expectedClasses=-1)</td></tr>
<tr class="separator:a6beef2c8d0972eaadad37abc89e74f95"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_methods_classtensorNet"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classtensorNet')"><img src="closed.png" alt="-"/>&#160;Protected Member Functions inherited from <a class="el" href="classtensorNet.html">tensorNet</a></td></tr>
<tr class="memitem:ab6e617d96e5542bef023ee9d4c96388a inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ab6e617d96e5542bef023ee9d4c96388a">tensorNet</a> ()</td></tr>
<tr class="memdesc:ab6e617d96e5542bef023ee9d4c96388a inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor.  <a href="classtensorNet.html#ab6e617d96e5542bef023ee9d4c96388a">More...</a><br /></td></tr>
<tr class="separator:ab6e617d96e5542bef023ee9d4c96388a inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a081b95210634e8ddb21e99d9ad1aa497 inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a081b95210634e8ddb21e99d9ad1aa497">ProfileModel</a> (const std::string &amp;deployFile, const std::string &amp;modelFile, const char *input, const <a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> &amp;inputDims, const std::vector&lt; std::string &gt; &amp;outputs, uint32_t maxBatchSize, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device, bool allowGPUFallback, nvinfer1::IInt8Calibrator *calibrator, std::ostream &amp;modelStream)</td></tr>
<tr class="memdesc:a081b95210634e8ddb21e99d9ad1aa497 inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Create and output an optimized network model.  <a href="classtensorNet.html#a081b95210634e8ddb21e99d9ad1aa497">More...</a><br /></td></tr>
<tr class="separator:a081b95210634e8ddb21e99d9ad1aa497 inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a088c3bf591e45e52ec227491f6f299ad inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a088c3bf591e45e52ec227491f6f299ad">PROFILER_BEGIN</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:a088c3bf591e45e52ec227491f6f299ad inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Begin a profiling query, before network is run.  <a href="classtensorNet.html#a088c3bf591e45e52ec227491f6f299ad">More...</a><br /></td></tr>
<tr class="separator:a088c3bf591e45e52ec227491f6f299ad inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac8582b9a6099e3265da4c3f9fdf804ea inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac8582b9a6099e3265da4c3f9fdf804ea">PROFILER_END</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:ac8582b9a6099e3265da4c3f9fdf804ea inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">End a profiling query, after the network is run.  <a href="classtensorNet.html#ac8582b9a6099e3265da4c3f9fdf804ea">More...</a><br /></td></tr>
<tr class="separator:ac8582b9a6099e3265da4c3f9fdf804ea inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae2e0ae17baf6e1975aaad7a7f5c60ce9 inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">PROFILER_QUERY</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:ae2e0ae17baf6e1975aaad7a7f5c60ce9 inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Query the CUDA part of a profiler query.  <a href="classtensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">More...</a><br /></td></tr>
<tr class="separator:ae2e0ae17baf6e1975aaad7a7f5c60ce9 inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-attribs"></a>
Protected Attributes</h2></td></tr>
<tr class="memitem:a80749925c9b6edf6b49043e8a0f507e3"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a80749925c9b6edf6b49043e8a0f507e3">mOutputClasses</a></td></tr>
<tr class="separator:a80749925c9b6edf6b49043e8a0f507e3"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:abd00b812a1f39a0bd23c43a8807d6193"><td class="memItemLeft" align="right" valign="top">std::vector&lt; std::string &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#abd00b812a1f39a0bd23c43a8807d6193">mClassSynset</a></td></tr>
<tr class="separator:abd00b812a1f39a0bd23c43a8807d6193"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9c75cea83d0c3e605aef8c0dd8e43177"><td class="memItemLeft" align="right" valign="top">std::vector&lt; std::string &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a9c75cea83d0c3e605aef8c0dd8e43177">mClassDesc</a></td></tr>
<tr class="separator:a9c75cea83d0c3e605aef8c0dd8e43177"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7bce88c4d67550b5d059a4b9cdbb90c1"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#a7bce88c4d67550b5d059a4b9cdbb90c1">mClassPath</a></td></tr>
<tr class="separator:a7bce88c4d67550b5d059a4b9cdbb90c1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aef7f06f334699634c33b1243c4352fc9"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470">NetworkType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classimageNet.html#aef7f06f334699634c33b1243c4352fc9">mNetworkType</a></td></tr>
<tr class="separator:aef7f06f334699634c33b1243c4352fc9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_attribs_classtensorNet"><td colspan="2" onclick="javascript:toggleInherit('pro_attribs_classtensorNet')"><img src="closed.png" alt="-"/>&#160;Protected Attributes inherited from <a class="el" href="classtensorNet.html">tensorNet</a></td></tr>
<tr class="memitem:a6bd429ccb1dc3717b2a4a5ad8e555cd0 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtensorNet_1_1Logger.html">tensorNet::Logger</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a6bd429ccb1dc3717b2a4a5ad8e555cd0">gLogger</a></td></tr>
<tr class="separator:a6bd429ccb1dc3717b2a4a5ad8e555cd0 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae1f74819d644d0f289253fbcf5d0655f inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtensorNet_1_1Profiler.html">tensorNet::Profiler</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae1f74819d644d0f289253fbcf5d0655f">gProfiler</a></td></tr>
<tr class="separator:ae1f74819d644d0f289253fbcf5d0655f inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a54005b86b851fa71aeb7a83d4ad32362 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a54005b86b851fa71aeb7a83d4ad32362">mPrototxtPath</a></td></tr>
<tr class="separator:a54005b86b851fa71aeb7a83d4ad32362 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7cb91e06b296431680d20e7e9fb0187d inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7cb91e06b296431680d20e7e9fb0187d">mModelPath</a></td></tr>
<tr class="separator:a7cb91e06b296431680d20e7e9fb0187d inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a11eeaa1e454a97a5634c7fb5ea1bc23d inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a11eeaa1e454a97a5634c7fb5ea1bc23d">mMeanPath</a></td></tr>
<tr class="separator:a11eeaa1e454a97a5634c7fb5ea1bc23d inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac040cf851463cd595a20a9400a5833c2 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac040cf851463cd595a20a9400a5833c2">mInputBlobName</a></td></tr>
<tr class="separator:ac040cf851463cd595a20a9400a5833c2 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aaa9ac0fae88a426f1a5325886da3b009 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#aaa9ac0fae88a426f1a5325886da3b009">mCacheEnginePath</a></td></tr>
<tr class="separator:aaa9ac0fae88a426f1a5325886da3b009 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a64fccb1894b0926e54a18fa47a271c70 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a64fccb1894b0926e54a18fa47a271c70">mCacheCalibrationPath</a></td></tr>
<tr class="separator:a64fccb1894b0926e54a18fa47a271c70 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Image recognition with classification networks, using TensorRT. </p>
</div><h2 class="groupheader">Member Enumeration Documentation</h2>
<a id="a0b7e93af566fe96bfc58cda5f4503470"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a0b7e93af566fe96bfc58cda5f4503470">&#9670;&nbsp;</a></span>NetworkType</h2>

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          <td class="memname">enum <a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470">imageNet::NetworkType</a></td>
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<p>Network choice enumeration. </p>
<table class="fieldtable">
<tr><th colspan="2">Enumerator</th></tr><tr><td class="fieldname"><a id="a0b7e93af566fe96bfc58cda5f4503470a9237dcd407a6df5b51f027b47053b013"></a>CUSTOM&#160;</td><td class="fielddoc"><p>Custom model provided by the user. </p>
</td></tr>
<tr><td class="fieldname"><a id="a0b7e93af566fe96bfc58cda5f4503470a3e774168f30b16946773a737a6c354cf"></a>ALEXNET&#160;</td><td class="fielddoc"><p>AlexNet trained on 1000-class ILSVRC12. </p>
</td></tr>
<tr><td class="fieldname"><a id="a0b7e93af566fe96bfc58cda5f4503470ab013750d9b65eacdae3c587dd42550c0"></a>GOOGLENET&#160;</td><td class="fielddoc"><p>GoogleNet trained 1000-class ILSVRC12. </p>
</td></tr>
<tr><td class="fieldname"><a id="a0b7e93af566fe96bfc58cda5f4503470af4a7d4831db43dda4de80c2a395f3ebb"></a>GOOGLENET_12&#160;</td><td class="fielddoc"><p>GoogleNet trained on 12-class subset of ImageNet ILSVRC12 from the tutorial. </p>
</td></tr>
<tr><td class="fieldname"><a id="a0b7e93af566fe96bfc58cda5f4503470a41ccbd9480e0072ed579da95eb6a479d"></a>RESNET_18&#160;</td><td class="fielddoc"><p>ResNet-18 trained on 1000-class ILSVRC15. </p>
</td></tr>
<tr><td class="fieldname"><a id="a0b7e93af566fe96bfc58cda5f4503470aa940343d369f0026258f0a42188a405b"></a>RESNET_50&#160;</td><td class="fielddoc"><p>ResNet-50 trained on 1000-class ILSVRC15. </p>
</td></tr>
<tr><td class="fieldname"><a id="a0b7e93af566fe96bfc58cda5f4503470a3bc3f084f3ef071585caf9629e64e24b"></a>RESNET_101&#160;</td><td class="fielddoc"><p>ResNet-101 trained on 1000-class ILSVRC15. </p>
</td></tr>
<tr><td class="fieldname"><a id="a0b7e93af566fe96bfc58cda5f4503470a91e56faa59f440c7aeb42f37363f27c4"></a>RESNET_152&#160;</td><td class="fielddoc"><p>ResNet-50 trained on 1000-class ILSVRC15. </p>
</td></tr>
<tr><td class="fieldname"><a id="a0b7e93af566fe96bfc58cda5f4503470a4a1ff14a90c30b505d6a2e563ad02bdc"></a>VGG_16&#160;</td><td class="fielddoc"><p>VGG-16 trained on 1000-class ILSVRC14. </p>
</td></tr>
<tr><td class="fieldname"><a id="a0b7e93af566fe96bfc58cda5f4503470ab44362ca647faaeb0b4a3124aef6a6fa"></a>VGG_19&#160;</td><td class="fielddoc"><p>VGG-19 trained on 1000-class ILSVRC14. </p>
</td></tr>
<tr><td class="fieldname"><a id="a0b7e93af566fe96bfc58cda5f4503470a196d67c5fe33ca0e6724b0dfdff0a8e0"></a>INCEPTION_V4&#160;</td><td class="fielddoc"><p>Inception-v4 trained on 1000-class ILSVRC12. </p>
</td></tr>
</table>

</div>
</div>
<h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a id="af6bd86e81ff9e67ffe19b575c17ed104"></a>
<h2 class="memtitle"><span class="permalink"><a href="#af6bd86e81ff9e67ffe19b575c17ed104">&#9670;&nbsp;</a></span>~imageNet()</h2>

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          <td>(</td>
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<p>Destroy. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a0ea17be1ce78b3e0758af46c970a968c">&#9670;&nbsp;</a></span>imageNet()</h2>

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          <td class="memname">imageNet::imageNet </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
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<h2 class="groupheader">Member Function Documentation</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#a11d6b18e0036ef5a329192f8b659dff9">&#9670;&nbsp;</a></span>Classify() <span class="overload">[1/2]</span></h2>

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          <td class="memname">int imageNet::Classify </td>
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          <td class="paramtype">float *&#160;</td>
          <td class="paramname"><em>rgba</em>, </td>
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          <td class="paramkey"></td>
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          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>width</em>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>height</em>, </td>
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          <td class="paramkey"></td>
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          <td></td>
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<p>Determine the maximum likelihood image class. </p>
<p>This function performs pre-processing to the image (apply mean-value subtraction and NCHW format), </p><dl class="section see"><dt>See also</dt><dd><a class="el" href="classimageNet.html#a83c68fbe0faab1e88abf07f7b535b8b9" title="Perform pre-processing on the image to apply mean-value subtraction and to organize the data into NCH...">PreProcess()</a> </dd></dl>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">rgba</td><td>float4 input image in CUDA device memory. </td></tr>
    <tr><td class="paramname">width</td><td>width of the input image in pixels. </td></tr>
    <tr><td class="paramname">height</td><td>height of the input image in pixels. </td></tr>
    <tr><td class="paramname">confidence</td><td>optional pointer to float filled with confidence value. </td></tr>
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<dl class="section return"><dt>Returns</dt><dd>Index of the maximum class, or -1 on error. </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a4295a052e7e4d12a369107a6525017a3">&#9670;&nbsp;</a></span>Classify() <span class="overload">[2/2]</span></h2>

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          <td class="memname">int imageNet::Classify </td>
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          <td class="paramtype">float *&#160;</td>
          <td class="paramname"><em>confidence</em> = <code>NULL</code></td><td>)</td>
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<p>Determine the maximum likelihood image class. </p>
<dl class="section note"><dt>Note</dt><dd>before calling this function, you must call <a class="el" href="classimageNet.html#a83c68fbe0faab1e88abf07f7b535b8b9" title="Perform pre-processing on the image to apply mean-value subtraction and to organize the data into NCH...">PreProcess()</a> with the image. </dd></dl>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">confidence</td><td>optional pointer to float filled with confidence value. </td></tr>
  </table>
  </dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>Index of the maximum class, or -1 on error. </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a27823449de3babc8b6eff1e916aff745">&#9670;&nbsp;</a></span>Create() <span class="overload">[1/3]</span></h2>

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          <td class="memname">static <a class="el" href="classimageNet.html">imageNet</a>* imageNet::Create </td>
          <td>(</td>
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        <tr>
          <td class="paramkey"></td>
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          <td class="paramtype">uint32_t&#160;</td>
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        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>precision</em> = <code><a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td>
          <td class="paramname"><em>device</em> = <code><a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
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          <td></td>
          <td>)</td>
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<p>Load a new network instance. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a9da8ad51bde43449ea159607ee97bb43">&#9670;&nbsp;</a></span>Create() <span class="overload">[2/3]</span></h2>

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          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>prototxt_path</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>model_path</em>, </td>
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        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>mean_binary</em>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>class_labels</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>input</em> = <code><a class="el" href="group__imageNet.html#ga00bb3120ef3040793ad3ee25d2727f5b">IMAGENET_DEFAULT_INPUT</a></code>, </td>
        </tr>
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          <td class="paramkey"></td>
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          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>output</em> = <code><a class="el" href="group__imageNet.html#ga74a585b96a1bd960b5201f6b69752fad">IMAGENET_DEFAULT_OUTPUT</a></code>, </td>
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        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>maxBatchSize</em> = <code><a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>precision</em> = <code><a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td>
          <td class="paramname"><em>device</em> = <code><a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></code>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>allowGPUFallback</em> = <code>true</code>&#160;</td>
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          <td></td>
          <td>)</td>
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<p>Load a new network instance. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">prototxt_path</td><td>File path to the deployable network prototxt </td></tr>
    <tr><td class="paramname">model_path</td><td>File path to the caffemodel </td></tr>
    <tr><td class="paramname">mean_binary</td><td>File path to the mean value binary proto (can be NULL) </td></tr>
    <tr><td class="paramname">class_labels</td><td>File path to list of class name labels </td></tr>
    <tr><td class="paramname">input</td><td>Name of the input layer blob. </td></tr>
    <tr><td class="paramname">output</td><td>Name of the output layer blob. </td></tr>
    <tr><td class="paramname">maxBatchSize</td><td>The maximum batch size that the network will support and be optimized for. </td></tr>
  </table>
  </dd>
</dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a84b96993a80be279067e0508f649e602">&#9670;&nbsp;</a></span>Create() <span class="overload">[3/3]</span></h2>

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          <td class="memname">static <a class="el" href="classimageNet.html">imageNet</a>* imageNet::Create </td>
          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>argc</em>, </td>
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          <td></td>
          <td class="paramtype">char **&#160;</td>
          <td class="paramname"><em>argv</em>&#160;</td>
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          <td></td>
          <td>)</td>
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<p>Load a new network instance by parsing the command line. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a42ce2aeeb96379bd04d94f65d483ece1">&#9670;&nbsp;</a></span>GetClassDesc()</h2>

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          <td>(</td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>index</em></td><td>)</td>
          <td> const</td>
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<p>Retrieve the description of a particular class. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a04276f915b0f40d6257cbed3fe47dc5f">&#9670;&nbsp;</a></span>GetClassPath()</h2>

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          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<p>Retrieve the path to the file containing the class descriptions. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a343bbe0aad580411900f811f30e8cbf7">&#9670;&nbsp;</a></span>GetClassSynset()</h2>

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          <td>(</td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>index</em></td><td>)</td>
          <td> const</td>
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<p>Retrieve the class synset category of a particular class. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a359ecefb8ac20cd44fddc69d38bde3ef">&#9670;&nbsp;</a></span>GetNetworkName()</h2>

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          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<p>Retrieve a string describing the network name. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#ad0cde8f64f32a50984c947dc823de04e">&#9670;&nbsp;</a></span>GetNetworkType()</h2>

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          <td class="memname"><a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470">NetworkType</a> imageNet::GetNetworkType </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<p>Retrieve the network type (alexnet or googlenet) </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a478f25126524a256e81ec264aad7e27a">&#9670;&nbsp;</a></span>GetNumClasses()</h2>

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          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<p>Retrieve the number of image recognition classes (typically 1000) </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a84dd4bae637b43560c6a1ca71e1df3fe">&#9670;&nbsp;</a></span>init() <span class="overload">[1/2]</span></h2>

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          <td class="memname">bool imageNet::init </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470">NetworkType</a>&#160;</td>
          <td class="paramname"><em>networkType</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>maxBatchSize</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>precision</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td>
          <td class="paramname"><em>device</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>allowGPUFallback</em>&#160;</td>
        </tr>
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          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
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<h2 class="memtitle"><span class="permalink"><a href="#aa5321e8082e2dc35f5982882fa284181">&#9670;&nbsp;</a></span>init() <span class="overload">[2/2]</span></h2>

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          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>prototxt_path</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>model_path</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>mean_binary</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>class_path</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>input</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>output</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>maxBatchSize</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>precision</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td>
          <td class="paramname"><em>device</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>allowGPUFallback</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
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<h2 class="memtitle"><span class="permalink"><a href="#a874e53e6172211c555031e50c6391f98">&#9670;&nbsp;</a></span>LoadClassInfo() <span class="overload">[1/2]</span></h2>

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          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>filename</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; std::string &gt; &amp;&#160;</td>
          <td class="paramname"><em>descriptions</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>expectedClasses</em> = <code>-1</code>&#160;</td>
        </tr>
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          <td>)</td>
          <td></td><td></td>
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<p>Load class descriptions from a label file. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#ab21eae64422a301712bf84252ede634d">&#9670;&nbsp;</a></span>LoadClassInfo() <span class="overload">[2/2]</span></h2>

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          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>filename</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; std::string &gt; &amp;&#160;</td>
          <td class="paramname"><em>descriptions</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; std::string &gt; &amp;&#160;</td>
          <td class="paramname"><em>synsets</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>expectedClasses</em> = <code>-1</code>&#160;</td>
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          <td>)</td>
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<p>Load class descriptions and synset strings from a label file. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a6beef2c8d0972eaadad37abc89e74f95">&#9670;&nbsp;</a></span>loadClassInfo()</h2>

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          <td>(</td>
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<h2 class="memtitle"><span class="permalink"><a href="#a911888acec5ff79f63e42ecdaed4d9c5">&#9670;&nbsp;</a></span>NetworkTypeFromStr()</h2>

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<p>Parse a string to one of the built-in pretrained models. </p>
<p>Valid names are "alexnet", "googlenet", "googlenet-12", or "googlenet_12", ect. </p><dl class="section return"><dt>Returns</dt><dd>one of the <a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470" title="Network choice enumeration. ">imageNet::NetworkType</a> enums, or <a class="el" href="classimageNet.html#a0b7e93af566fe96bfc58cda5f4503470a9237dcd407a6df5b51f027b47053b013" title="Custom model provided by the user. ">imageNet::CUSTOM</a> on invalid string. </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a0a6ed78a812c2c8847aec7e2c9c7ecab">&#9670;&nbsp;</a></span>NetworkTypeToStr()</h2>

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<p>Convert a NetworkType enum to a string. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a83c68fbe0faab1e88abf07f7b535b8b9">&#9670;&nbsp;</a></span>PreProcess()</h2>

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<p>Perform pre-processing on the image to apply mean-value subtraction and to organize the data into NCHW format and BGR colorspace that the networks expect. </p>
<p>After calling <a class="el" href="classimageNet.html#a83c68fbe0faab1e88abf07f7b535b8b9" title="Perform pre-processing on the image to apply mean-value subtraction and to organize the data into NCH...">PreProcess()</a>, you can call <a class="el" href="classimageNet.html#a11d6b18e0036ef5a329192f8b659dff9" title="Determine the maximum likelihood image class. ">Classify()</a> without supplying all the parameters. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#ad9eb86e82a3a2a05700e3c36f9554e64">&#9670;&nbsp;</a></span>Process()</h2>

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<p><a class="el" href="classProcess.html" title="Static functions for retrieving information about the running process. ">Process</a> the network, without determining the classification argmax. </p>
<p>To perform the actual classification via post-processing, <a class="el" href="classimageNet.html#a11d6b18e0036ef5a329192f8b659dff9" title="Determine the maximum likelihood image class. ">Classify()</a> should be used instead. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a7629a888728ef94bf35e573a96ebe4bd">&#9670;&nbsp;</a></span>Usage()</h2>

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<p>Usage string for command line arguments to <a class="el" href="classimageNet.html#a27823449de3babc8b6eff1e916aff745" title="Load a new network instance. ">Create()</a> </p>

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<h2 class="groupheader">Member Data Documentation</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#a9c75cea83d0c3e605aef8c0dd8e43177">&#9670;&nbsp;</a></span>mClassDesc</h2>

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<h2 class="memtitle"><span class="permalink"><a href="#aef7f06f334699634c33b1243c4352fc9">&#9670;&nbsp;</a></span>mNetworkType</h2>

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<hr/>The documentation for this class was generated from the following file:<ul>
<li>jetson-inference/<a class="el" href="imageNet_8h_source.html">imageNet.h</a></li>
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